Curve Boxplot : Generalization of Boxplot for Ensembles of Curves

In simulation science, computational scientists often study the behavior of their simulations by repeated solutions with variations in parameters and/or boundary values or initial conditions. Through such simulation ensembles, one can try to understand or quantify the variability or uncertainty in a...

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Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1998. - 20(2014), 12 vom: 26. Dez., Seite 2654-63
1. Verfasser: Mirzargar, Mahsa (VerfasserIn)
Weitere Verfasser: Whitaker, Ross T, Kirby, Robert M
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2014
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article
Beschreibung
Zusammenfassung:In simulation science, computational scientists often study the behavior of their simulations by repeated solutions with variations in parameters and/or boundary values or initial conditions. Through such simulation ensembles, one can try to understand or quantify the variability or uncertainty in a solution as a function of the various inputs or model assumptions. In response to a growing interest in simulation ensembles, the visualization community has developed a suite of methods for allowing users to observe and understand the properties of these ensembles in an efficient and effective manner. An important aspect of visualizing simulations is the analysis of derived features, often represented as points, surfaces, or curves. In this paper, we present a novel, nonparametric method for summarizing ensembles of 2D and 3D curves. We propose an extension of a method from descriptive statistics, data depth, to curves. We also demonstrate a set of rendering and visualization strategies for showing rank statistics of an ensemble of curves, which is a generalization of traditional whisker plots or boxplots to multidimensional curves. Results are presented for applications in neuroimaging, hurricane forecasting and fluid dynamics
Beschreibung:Date Completed 20.05.2016
Date Revised 11.09.2015
published: Print
Citation Status MEDLINE
ISSN:1941-0506
DOI:10.1109/TVCG.2014.2346455